DEVELOPED BY PESTPREDICT · 2017. 3. 28. · MOBIN AHMAD1, PRADEEP PRAJAPATI , ABHINAV SINGH ,...
Transcript of DEVELOPED BY PESTPREDICT · 2017. 3. 28. · MOBIN AHMAD1, PRADEEP PRAJAPATI , ABHINAV SINGH ,...
NCIPM
MOBILE APPLICATION FOR FORECAST OF INSECT PESTS AND DISEASES OF RICE, PIGEONPEA, GROUNDNUT & TOMATO
PESTPREDICT
RICA –NC PI M
t ona I n vations in Cl
Na i l n o
Pest Pre ict n Empiric l Model
d ioa
ima e Resi ent Ag i u ture
t li
r c l
B s d S s e (P s Pre ict E S
a e y t m e t d - M ) NI RA ICAR–NCIPM
National Innovations in ClPest Prediction Empirical Model
imate Resilient AgricultureBased System (PestPredict-EMS)
NI RA
1VENNILA S , ANKUR TOMAR , MANISHA BAGRI , 1 1GAJAB SINGH , SATISH KUMAR YADAV ,
1 2NIRANJAN SINGH , GIRISH KUMAR JHA , 2 2 1AMRENDER JHA , DK DAS , ALPANA KUMARI ,
1 1PURAN CHANDRA , HIMANSHI DWIVEDI , 1MOBIN AHMAD , PRADEEP PRAJAPATI ,
1 3ABHINAV SINGH , ARJIT SAHA , MS RAO 3AND M PRABHAKAR
Lal Bahadur Shastri Building, New Delhi
New Delhi
Hyderabad
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1ICAR-National Research Centre for
Integrated Pest Management
2ICAR-Indian Agricultural Research Institute
3ICAR-Central Research Institute for
Dryland Agriculture
DEVELOPED BY
PUBLISHED BY
DirectorICAR-NCIPM, LBS Building, Pusa Campus, New Delhi-110012http://www.ncipm.orgin/nicra
CONTRIBUTORS TO THE
PEST WEATHER DATABASE FOR
TARGET CROPS FROM
DIFFERENT LOCATIONS
ARE GRATEFULLY ACKNOWLEDGED
RULE BASED PREDICTIONS
RICE
Yellow Stem Borer Brown Plant Hopper Green Leaf Hopper
Leaf Hopper WBP Hopper Caseworm
GROUNDNUT
Tobacco Caterpillar
TOMATO
Early Leaf Blight
DOWNLOAD THE APP
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Scan the QR CodesDownload & InstallStart using as per needAlso Web Enabled at http://www.ncipm.org.in/ nicra/ForewarningSystem/Login.aspx
PREDICTIONS BASED ON EMPIRICAL MODELS
Crop Insect Beneficial
Rice 10 01 04
Pigeonpea 06 02 05
Groundnut 06 01 04
Tomato 07 01 11
Disease
RBS EMS
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‘PESTPREDICT’ is a mobile based
application making weather based
pest forewarning as a component of
integrated pest management in the
area of crop protection.
Approaches to forewarning
– Rule based predictions
– Empirical Models
Validated forecast models of insect
pests and diseases are built in the
PESTPREDICT.
Operating System: Android
Platform: Google (SDK)
Language: Core Java
Software: Eclipse Juno (ADT)
Version: 4.1 (Jelly Bean)
Source: Open Source Standalone
App
TECHNICAL FEATURES
RICE
PIGEONPEA
GROUNDNUT
TOMATO
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Ludhiana — Punjab
Chinsurah — West Bengal
Raipur — Chhattisgarh
Karjat — Maharashtra
Hyderabad — Telangana
Mandya — Karnataka
Aduthurai — Tamil Nadu
SK Nagar — Gujarat
Jabalpur — Madhya Pradesh
Warangal — Telangana
Gulbarga — Karnataka
Anantapur — Andhra Pradesh
Vamban — Tamil Nadu
Junagadh — Gujarat
Jalgaon — Maharashtra
Dharwad — Karnataka
Kadiri — Andhra Pradesh
Vridhachalam — Tamil Nadu
Ludhiana — Punjab
Varanasi — Uttar Pradesh
Kalyani — West Bengal
Raipur — Chhattisgarh
Rahuri — Maharashtra
Hyderabad — Andhra Pradesh
Bengaluru — Karnataka
CROPS & LOCATIONS OF PESTPREDICT PURPOSE
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Issue of ‘Pest Alerts’ to crop growers.
Potential stakeholders – Researchers,
extension agents and farmers.
Facilitates prediction of insect pest
dynamics for the current and future
climate periods relating to emission
scenario database of Intergovern-
mental Panel of Climate Change
(IPCC).
CAUTION
ACCURACY OF PESTPREDICT DEPENDS
ON QUALITY OF WEATHER INPUTS AND
VARIES DEPENDING ON OTHER BIOTIC
VARIABLES OR EXTREMES OF WEATHER
EVENTS.